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---
datasets:
- ajibawa-2023/Code-290k-ShareGPT
language:
- en
tags:
- code
license: other
---
**Code-290k-6.7B-Instruct**
This model is trained on [DeepSeek-Coder-6.7B-Instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct). I have used my existing dataset [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT) for training purpose.
It is trained on around 290000 set of codes. Along with Python, Java, JavaScript, GO, C++, Rust, Ruby, Sql, MySql, R, Julia, Haskell, etc. code with detailed explanation is used for training purpose.
This model utilises Alpaca format. Besides code generation it will also give you explanation.
**Training:**
Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took 85 hours. DeepSeek-Coder codebase and DeepSpeed was used for training purpose.
This is a full fine tuned model.
Links for quantized models are given below.
**Exllama**
Exllama v2:[Link](https://huggingface.co/bartowski/Code-290k-6.7B-Instruct-exl2)
Extremely thankful to [Bartowski](https://huggingface.co/bartowski) for making Quantized version of the model.
**Example Prompt**:
```
This is a conversation with your helpful AI assistant. AI assistant can generate Code in various Programming Languages along with necessary explanation.
### Instruction:
{instruction}
### Response:
```
You can modify above Prompt as per your requirement. I have used Alpaca format.
I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
Thank you for your love & support.
**Examples**
1. **Bayes Theorem - Python**
2. **Fermat's little theorem**
3. **The Arrhenius equation using R**
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